Abstract: A data localization service is provided for a web browser residing on a computing device. Depending upon the availability of the network connection as well as the level of native support in the browser, the data localization service will support different levels of service/performance to optimize the user experience. To do so, the data localization service includes a priority handler configured to receive a request to localize data from a requesting client application and provide in response thereto a localized representation of the data to the requesting client application. The data localization service may also include a native data localizer configured to receive a request to localize data from the priority handler and localize the data in accordance with a localization preference parameter indicative of a locale. The native data localizer may be a function integrated into the script interpreter of the web browser.

Abstract: A data localization service is provided for a web browser residing on a computing device. Depending upon the availability of the network connection as well as the level of native support in the browser, the data localization service will support different levels of service/performance to optimize the user experience. To do so, the data localization service includes a priority handler configured to receive a request to localize data from a requesting client application and provide in response thereto a localized representation of the data to the requesting client application. The data localization service may also include a native data localizer configured to receive a request to localize data from the priority handler and localize the data in accordance with a localization preference parameter indicative of a locale. The native data localizer may be a function integrated into the script interpreter of the web browser.

Abstract: Method for hyper-spectral imaging and analysis of a sample of matter, for identifying and characterizing an object of interest therein. Preparing test solution or suspension of the sample, including adding thereto a spectral marker specific to object of interest, such that if object of interest is in test solution or suspension, object of interest becomes a hyper-spectrally active target which is hyper-spectrally detectable and identifiable; adding to test solution or suspension a background reducing chemical, for reducing background interfering effects caused by presence of objects of non-interest in test solution or suspension, thereby increasing hyper-spectral detectability of hyper-spectrally active target in test solution or suspension; generating and collecting hyper-spectral image data and information of test solution or suspension; and, processing and analyzing thereof.

Abstract: Method for hyper-spectral imaging and analysis of a sample of matter, for identifying and characterizing an object of interest therein. Preparing test solution or suspension of the sample, including adding thereto a spectral marker specific to object of interest, such that if object of interest is in test solution or suspension, object of interest becomes a hyper-spectrally active target which is hyper-spectrally detectable and identifiable; adding to test solution or suspension a background reducing chemical, for reducing background interfering effects caused by presence of objects of non-interest in test solution or suspension, thereby increasing hyper-spectral detectability of hyper-spectrally active target in test solution or suspension; generating and collecting hyper-spectral image data and information of test solution or suspension; and, processing and analyzing thereof.

Abstract: Method for hyper-spectral imaging and analysis of a sample of matter, for identifying and characterizing an object of interest therein. Preparing test solution or suspension of the sample, including adding thereto a spectral marker specific to object of interest, such that if object of interest is in test solution or suspension, object of interest becomes a hyper-spectrally active target which is hyper spectrally detectable and identifiable; adding to test solution or suspension a background reducing chemical, for reducing background interfering effects caused by presence of objects of non-interest in test solution or suspension, thereby increasing hyper spectral detectability of hyper spectrally active target in test solution or suspension; generating and collecting hyper-spectral image data and information of test solution or suspension; and, processing and analyzing thereof.

Abstract: Embodiments of the present invention can gather data from native language sources to produce a valid collation sequence that is appropriate for a particular language and application. Sequences of characters in this data are tested to determine strength levels used by the given language. The data is also recursively probed with other sequences to test for contractions and identify expansions. Sequences in the data may then be compared against a known or predetermined sequence to generate a set of sorting rules that is specific to the language and application. The rules are formatted to replicate the sorting order found in the data.

Abstract: Method for hyper-spectral imaging and analysis of a sample of matter, for identifying and characterizing an object of interest therein. Preparing test solution or suspension of the sample, including adding thereto a spectral marker specific to object of interest, such that if object of interest is in test solution or suspension, object of interest becomes a hyper-spectrally active target which is hyper spectrally detectable and identifiable; adding to test solution or suspension a background reducing chemical, for reducing background interfering effects caused by presence of objects of non-interest in test solution or suspension, thereby increasing hyper spectral detectability of hyper spectrally active target in test solution or suspension; generating and collecting hyper-spectral image data and information of test solution or suspension; and, processing and analyzing thereof.

Abstract: Embodiments of the present invention can gather data from native language sources to produce a valid collation sequence that is appropriate for a particular language and application. Sequences of characters in this data are tested to determine strength levels used by the given language. The data is also recursively probed with other sequences to test for contractions and identify expansions. Sequences in the data may then be compared against a known or predetermined sequence to generate a set of sorting rules that is specific to the language and application. The rules are formatted to replicate the sorting order found in the data.